Wanted to share an excellent piece from @rtelford that I think many here will appreciate. It’s a very thoughtful and well-structured look at dilution risk in microcaps, with several smart components that come together into a practical framework for evaluation.
“How to Avoid Dilution in Microcaps – A Dilution Risk Scorecard”
https://microcapclub.com/how-to-avoid-dilution-in-microcaps-a-dilution-risk-scorecard/?ref=newsletter
Ryan has a real talent for breaking down complex risk factors into something clear, intuitive, and actionable. His work always shows a high level of care, experience, and analytical depth, and this piece is another great example.
Big thanks to Ryan for continuing to produce such high-quality research based on the tools in Portfolio123 and for sharing it with the community.
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Has anyone built this scorecard in P123, before I attempt to reconstruct? Thanks
I tried implementing something similar some time ago in my Portfolio123 universes based on these findings. In the ones where I already apply some previous soft quality filtering (e.g. basic profitability, balance sheet strength, ....), adding the dilution scorecard didn't meaningfully improve results. It seems somewhat redundant once you've already filtered for higher-quality microcaps.
I suspect it would be more powerful in a broader, less-filtered universe where dilution risk is a bigger differentiator. Might go back and test it that way.
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I created a ranking system based on this a few months ago. I don’t recall if I put much effort into it, so not sure how accurate it is. I made it public: rank sys
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It was discussed some time ago.
The higher the lower risk of dillution:
isna((OperCashFlTTM > 0) + (Eval(FCFTTM >= 0, 1, CashEquivQ / Abs(FCFTTM) > 1)) + (SharesQ / SharesPYQ < 1.03) + ((SharesFDQ - SharesQ) / SharesQ < 0.05) + (CurRatioQ > 1.5), 0)
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